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Lookup NU author(s): Paul Simavari, Dr Kayvan PazoukiORCiD, Dr Rosemary NormanORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Understanding vessel energy demand requires knowledge of vessel motion relative to the surrounding water, rather than motion relative to the Earth’s surface. However, direct measurements of speed through water (STW) are rarely accessible beyond individual vessels, as they rely on onboard instrumentation and are not publicly available. As a result, studies of vessel energy consumption and zero-emission transition pathways in inland waterway transport (IWT) often rely on Automatic Identification System (AIS) data, which provides speed over ground (SOG) but does not account for environmental current effects. The objective of this study is to develop an inferential method to estimate STW using sparse publicly available data. The proposed method combines AIS-derived vessel trajectories with a modelled environmental current field derived from tidal elevation data to resolve the component of the current acting along the vessel’s direction of travel. Vessel motion is reconstructed from AIS position data, and the along-track current component is obtained through vector projection onto the vessel trajectory. Combining this with observed SOG enables estimation of STW without onboard measurements. The method is evaluated using representative vessel case studies on the tidal River Thames, where estimated STW is compared with independent Doppler-based measurements. A detailed validation is presented for one representative vessel, with additional validation undertaken across multiple vessel types operating under different conditions. Across the validation cases, the methodology shows strong agreement with measured STW, demonstrating that STW can be estimated with acceptable accuracy using widely available data. This establishes the physical foundation required for subsequent propulsion power and energy-demand assessment in data-constrained environments.
Author(s): Simavari P, Pazouki K, Norman R
Publication type: Article
Publication status: Published
Journal: Journal of Marine Science and Engineering
Year: 2026
Volume: 14
Issue: 15
Pages: 1442
Online publication date: 06/08/2026
Acceptance date: 28/07/2026
Date deposited: 10/08/2026
ISSN (electronic): 2077-1312
Publisher: MDPI AG
URL: https://doi.org/10.3390/jmse14151442
DOI: 10.3390/jmse14151442
Data Access Statement: The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
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